Markerless human motion tracking from a single camera using Interval Particle Filte

Jamal Saboune 1 François Charpillet 1
1 MAIA - Autonomous intelligent machine
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : In this paper we present a new approach for marker less human motion capture from conventional camera feeds. The aim of our study is to recover 3D positions of key points of the body that can serve for gait analysis. Our approach is based on foreground extraction, an articulated body model and particle filters. In order to be generic and simple, no restrictive dynamic modeling was used. A new modified particle-filtering algorithm was introduced. It is used efficiently to search the model configurations space. This new algorithm, which we call Interval Particle Filtering, reorganizes the configurations search space in an optimal deterministic way and proved to be efficient in tracking natural human movement. Results for human motion capture from a single camera are presented and compared to results obtained from a marker based system. The system proved to be able to track motion successfully even in partial occlusions and even outdoors.
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Article dans une revue
International Journal on Artificial Intelligence Tools, World Scientific Publishing, 2007, 6 (4), pp. 593-609. 〈10.1142/S021821300700345X〉
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https://hal.inria.fr/inria-00175667
Contributeur : François Charpillet <>
Soumis le : samedi 29 septembre 2007 - 15:19:05
Dernière modification le : jeudi 11 janvier 2018 - 06:19:51

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Jamal Saboune, François Charpillet. Markerless human motion tracking from a single camera using Interval Particle Filte. International Journal on Artificial Intelligence Tools, World Scientific Publishing, 2007, 6 (4), pp. 593-609. 〈10.1142/S021821300700345X〉. 〈inria-00175667〉

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